FIND's content model presents some unique challenges that make it more complex than many other content-driven websites. The most obvious challenge is the use of bilingual content throughout, but that's fairly easy to handle by simply storing separate fields for Arabic and English texts.
FIND supports several types of narratives, from simple monolithic texts like this blog post, to more complex, segmented stories that incorporate many types of media.
Photography is an important aspect of FIND, and a large amount of the complexity in the data model is related to presenting photographic images as attractively as possible on a broad range of different devices. Any given photograph may have many representations for different aspect ratios and capabilities. Square cropped photos, wide cropped photos, and animated representations are among the alternatives. Since the same photo may be used in different contexts to illustrate different concepts, individual bilingual captions can be created for each usage.
An extensive story like
"The Abu Dhabi Bus Station" is composed of many smaller parts: short narratives, photographs, and segments of HTML for video and audio embeds. Each of those parts is managed and rendered as a small story of its own.
Most importantly, the FIND website also must facilitate the mission of "Forming Intersections and Dialogues" by developing connections between atoms of content. We followed the current of social media by adopting the hashtag as our mechanism for these interconnections. No matter its complexity, each narrative, its component parts, and its creators can all be related to many hashtags in the FIND database.
In turn, each of those hashtag relationships optionally has a strength, allowing the website to algorithmically discover the best connections between content, authors, and cross-cutting abstract concepts.
An automated social media discovery engine parses hashtags typed into social media posts (e.g.
#FIND_Solertium) and automatically makes the connections back to the associated concepts in the FIND database.
One exciting nuance is that FIND's hashtag database is itself bilingual, maintaining both English and Arabic representations of each hashtag. So regardless of whether an author or social media poster writes in English or Arabic, FIND discovers the same connections.
As FIND grows and its social footprint increases, we are just beginning to discover the possibilities inherent in our content model, and are working hard to find ever-better ways to navigate and visualize the intersections revealed.
